comp-analysis

# /comp-analysis Analyze compensation data for benchmarking, band placement, and planning. Helps benchmark compensation against market data for hiring, retention, and equity planning. ## Usage ``` /comp-analysis $ARGUMENTS ``` ## What I Need From You **Option A: Single role analysis** "What should we pay a Senior Software Engineer in SF?" **Option B: Upload comp data** Upload a CSV or paste your comp bands. I'll analyze placement, identify outliers, and compare to market. **Option C: Equity modeling** "Model a refresh grant of 10K shares over 4 years at a $50 stock price." ## Compensation Framework ### Components of Total Compensation - **Base salary**: Cash compensation - **Equity**: RSUs, stock options, or other equity - **Bonus**: Annual target bonus, signing bonus - **Benefits**: Health, retirement, perks (harder to quantify) ### Key Variables - **Role**: Function and specialization - **Level**: IC levels, management levels - **Location**: Geographic pay adjustments - **Company stage**: Startup vs. growth vs. public - **Industry**: Tech vs. finance vs. healthcare ### Data Sources - **With ~~compensation data**: Pull verified benchmarks - **Without**: Use web research, public salary data, and user-provided context - Always note data freshness and source limitations ## Output Provide percentile bands (25th, 50th, 75th, 90th) for base, equity, and total comp. Include location adjustments and company-stage context. ```markdown ## Compensation Analysis: [Role/Scope] ### Market Benchmarks | Percentile | Base | Equity | Total Comp | |------------|------|--------|------------| | 25th | $[X] | $[X] | $[X] | | 50th | $[X] | $[X] | $[X] | | 75th | $[X] | $[X] | $[X] | | 90th | $[X] | $[X] | $[X] | **Sources:** [Web research, compensation data tools, or user-provided data] ### Band Analysis (if data provided) | Employee | Current Base | Band Min | Band Mid | Band Max | Position | |----------|-------------|----------|----------|----------|----------| | [Name] | $[X] | $[X] | $[X] | $[X] | [Below/At/Above] | ### Recommendations - [Specific compensation recommendations] - [Equity considerations] - [Retention risks if applicable] ``` ## If Connectors Available If **~~compensation data** is connected: - Pull verified market benchmarks by role, level, and location - Compare your bands against real-time market data If **~~HRIS** is connected: - Pull current employee comp data for band analysis - Identify outliers and retention risks automatically ## Tips 1. **Location matters** — Always specify location for benchmarking. SF vs. Austin vs. London are very different. 2. **Total comp, not just base** — Include equity, bonus, and benefits for a complete picture. 3. **Keep data confidential** — Comp data is sensitive. Results stay in your conversation.